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In this paper, the degree of polarization of the fluorescent L X-ray lines L ℓ , Lα1 and Lα2, is studied theoretically with respect to incident energy for some high-Z elements from tungsten to Uranium. The linear polarization for each characteristic line is evolved through alignment parameter assessed by nonrelativistic dipole approximation (NDA) in a point Coulomb potential (A20), and accommodating the effect of screening in a screened Coulomb potential (A20*) and analytical perturbation theory (A20**). The values of degree of linear polarization predicted using alignment parameters (A20,A20*and A20**) are not exactly the same as reported by Kämpfer et al. (Phys Rev A 93:033409, 2016) but the trends are almost the same. Since alignment is model sensitive, therefore, the degree of linear polarization will also be dependent on the theoretical approximation/model used. For L ℓ lines, polarization is found to be in the range (12 to 43) %, whereas for the Lα1 line, the ultimate vigorous line of the L-shell emission, the estimated polarization is positive with value range from (+ 2.5 to + 7.5)% and for the Lα2 line the polarization is negative with value range from (− 9.5 to − 27) %. These calculations are in exemplary compromise with the earlier theoretical results and manifest barely a feeble vulnerability of polarization on the vibrancy of the incident radiation. The present polarization trends show resemblance with the results of Kämpfer et al. (2016) and Özdemir et al. (Appl Radiat Isotopes 69:991, 2011), although the values are not absolutely matching. [ABSTRACT FROM AUTHOR]

A total of 158 serum samples of newly diagnosed type 2 diabetes patients and control subjects were analyzed using Synchrotron Radiation X-ray Fluorescence (SRXRF) technique. The microprobe XRF beam line-16 of Indus-2 synchrotron radiation facility at Raja Ramanna Centre for Advanced Technology (RRCAT), Indore, India, was used to identify and quantify the elements K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb, Sr, and Pb. A significant decrease in the mean concentrations of K, Ca, Ti, Cr, Mn, Ni, Zn, and As and an increase in the concentrations of V, Fe, Co, Cu, Se, and Pb were observed in the serum samples of the patient group when compared to the control group. It is hypothesized that the observed alterations in the elemental concentrations might have led to ineffective uptake of insulin and have interfered with glucose homeostasis by either directly or indirectly causing oxidative stress. [ABSTRACT FROM AUTHOR]

In this study, we present X-ray absorption near edge structure (XANES) for four different layered transition metal dichalcogenide compounds, (i) pure NbSe 2 , (ii) NbSe 2 with Se vacancy, (iii) impure NbSe 2 with Cr defects, and (iv) impure NbSe 2 with Fe defects. Density functional theory based computed Se and Nb K-edge XANES are compared with their experimental counterparts. Theoretical spectra very well reproduce the observed trends of the experimental spectra. Our calculations in presence and absence of core-hole effect are presented separately, to understand the role of core-hole in determining XANES for these materials. In general, theoretically computed XANES spectra in the absence of core-hole effect agree significantly better with the experimentally observed one. All the absorption spectra consist of several peaked features of particular significance, which are thoroughly analyzed in terms of the unoccupied partial density of states. Presence of magnetic impurities like Fe, Cr cause inter-layer as well as intra-layer charge transfer. Bader charge analysis show that, more and more charges are gained by Se atom with increasing Cr defect concentration which shifts its absorption edge to lower photon energy. Whereas, loss of charge by Se atom with increasing Fe impurity shifts the corresponding absorption edge to higher photon energy. Nb atom gains charge in presence of Fe/Cr defects resulting its edge to shift to lower photon energy. These trends in absorption edge shift are similar in theoretical as well as in experimental spectra. We also provide theoretical prediction of Nb L 2 -edge which accesses Nb-d states that are relevant for superconductivity. [ABSTRACT FROM AUTHOR]

The nutrient profiling of green leafy vegetables is largely concentrated on biochemical assays and their elemental composition is often overlooked. At the same time, the investigation of the elemental composition of plants is essential, as they are required in several metabolic processes for the normal growth and development of the human body and their deficiency can lead to several clinical disorders. In this paper, we consider the potential of the synchrotron-radiation-induced energy dispersive X-ray fluorescence spectroscopy technique as a rapid, sensitive, and simultaneous multielemental detection tool to investigate the elemental composition of different elements present in some leafy vegetables: dill, fenugreek, mustard, and chenopodium. The X-ray fluorescence spectrа of the leaves of dill, fenugreek, mustard, and chenopodium were excited by synchrotron X-ray radiation having an energy of 15 keV and recorded in the energy range <20 keV. The recorded spectrum shows the presence of potassium, calcium, manganese, iron, nickel, copper, zinc, arsenic, and selenium with varying concentrations in different leafy vegetables. PyMca software was applied to determine the concentration of the various detected elements. The relative quantitative comparison of the detected elements shows that chenopodium leaves are a rich source of potassium among all the leafy vegetables studied. The leaves of mustard and chenopodium are abundant in calcium, while the leaves of dill and fenugreek have a higher content of trace elements like manganese, iron, copper, nickel, selenium and zinc. Herein, the role of the detected elements in human and plant health is also described. [ABSTRACT FROM AUTHOR]

Original Equipment Manufacturers (OEM) that assemble multiple durable products are actively engaged in adopting remanufacturing practices. This study addresses the introduction of a new business proposal, which is carrying out remanufacturing of components from acquired returns by an OEM through the set-up of required Reverse Flow Capacities (RFC), which are capacities for dismantling the returns and capacities for remanufacturing various components. Hence, by incorporating the activity on remanufacturing of components, an OEM creates a new cheaper source for obtaining components, in addition to the conventional sources of manufacturing and/or purchasing. The components obtained from any of these three sources can be used to assemble the multiple durable products for satisfying demands. The study refers to this problem as "Multi Products–Component Remanufacturing (MP-CR) problem". Furthermore, it is identified that the incorporation of MP-CR problem has tremendous potential in the Indian automobile sector. With these, this study address two strategic issues and an operation issue for the incorporation of new MP-CR problem to an OEM. The first strategic issue is the determination of RFC that must be set-up. This strategic issue is addressed in synchronize with the operational issue of determining the optimal Inventory & Production Plans (I&PP) for assembling multiple products for a given planning horizon. In addition, once the optimal RFC is determined, the second strategic issue is the determination of optimal period (called as Breakeven Period (BEP)), after which the OEM would reclaim the capital investment for setting-up the optimal RFC. In order to address these three interrelated decisions, a systematic methodology is proposed. In the proposed methodology, first an Integer Linear Programming Model is developed for the existing system of the OEM to determine the optimal I&PP. Next, this model is extended to determine the optimal RFC and corresponding optimal I&PP. The solution from both proposed models are used for obtaining the Breakeven Period (BEP), which indicates when the capital investments breakeven. Finally, the proposed methodology is demonstrated by developing suitable data observed from an Indian Automobile OEM. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic ship berth allocation problem for a container handling port, focusing on vessel waiting time at the anchorage due to the unavailability of the berth and quay cranes. A mixed integer linear programming model considering the fuel cost associated with waiting time and operational time of the docked vessel is developed. The hiring of the quay cranes to load/unload the containers from the ship and arrangement of the vessels in different berths is taken into account. Fuel consumed by the vessels while performing their respective port operations is incorporated in the model for addressing the sustainability aspects in berth allocation problem. A chemical reaction optimization algorithm is proposed to solve the problem in a large-scale realistic environment and compared with the results with block-based genetic algorithm, genetic algorithm and particle swarm optimization. The computational experiment illustrates and validates the proposed model on a real case scenario of the port located in India. The case shows that the developed model achieves better utilization of port resources and available berths. [ABSTRACT FROM AUTHOR]

X-ray reflectivity of single layer coated X-ray mirror is confined to small grazing angles (< 1°) grazing incidence X-ray telescopes usually are bulky and have large focal lengths in trade of effective area which is expensive for a space based telescope. Critical angle for total external reflection of a mirror varies inversely with the energy of the incident photon. This practically limits the possibility of making an X-ray telescope sensitive to higher energy X-rays (<10keV). Use of multilayer mirrors makes it possible to operate the instrument at higher angles and also significantly improves the high energy sensitivity (80 keV). Fabricated W/B4C multilayer mirror provides a peak reflectivity of 19% at first Bragg peak (2.3°) when tested with 8.047 keV X-rays. Multi-wavelength reflectivity analysis of W/B4C multilayer mirror from 9 to 16 keV is presented with a discussion on applications of multilayer mirrors in high energy astronomy. [ABSTRACT FROM AUTHOR]

In this paper a study on the operations of a bulk material port is carried out to develop a decision support model, which deals with the dynamics of port and aids in better decision making at different scenarios. Here, we describe various decisions taken by port authorities pertaining to the import of coal at the terminal. We optimize these decisions with the aim of minimizing the unloading time of ships at the port, congestion in the stockyard, and loading time of the rakes. A practice-oriented decision support model is proposed to assist port planners in making these decisions. Various operational rules are embedded within the model, for carrying out the modelling of various port operations. The utility of the developed model is demonstrated using a case study which helps in achieving efficient utilization of berths, stockyard and rake loading stations. [ABSTRACT FROM AUTHOR]

Virtual Cellular Manufacturing System is a new type of cellular system that emerged as a promising alternative for designing cells in real time. The problem is complex and time consuming NP-hard problem in its nature. This study was conducted to design virtual cells that maximizes similarity index and minimizes lead time. A mathematical model and an effective solution procedure were proposed. Several randomly generated data sets were used along a case study to test the performance of the proposed approach. The effects of inherent parameters of virtual systems were investigated and compared by using particular performance measures. [ABSTRACT FROM AUTHOR]

We present diurnal variation of ambient ammonia (NH3) in relation with other trace gases (O3, CO, NO, NO2, and SO2) and meteorological parameters at an urban site of Delhi during winter period. For the first time, ambient ammonia (NH3) was monitored very precisely and continuously using ammonia analyzer, which operates on chemiluminescence method. NH3 estimation efficiency of the chemiluminescence method (>90%) is much higher than the conventional chemical trapping method (reproducibility 4.5%). Ambient NH3 concentration reaches its maxima (46.17 ppb) at night and minimum during midday. Result reveals that the ambient ammonia (NH3) concentration is positively correlated with ambient NO ( r2 = 0.79) and NO2 ( r2 = 0.91) mixing ratio and negatively correlated with ambient temperature ( r2 = − 0.32). Wind direction and wind speed indicates that the nearby (~500 m NW) agricultural fields may be major source of ambient NH3 at the observational site. [ABSTRACT FROM AUTHOR]

This paper deals with the multi-agent system for distributed computer-aided process planning problem. The proposed architecture consists of three autonomous agents (Global Manager Agent, Design Agent, and Optimization Agent) capable of communicating to each other through eXtensible Markup Language (XML). In contrast to the traditional process planning model, a new paradigm incorporating fixture cost has been conceptualized. Optimization agent is facilitated by the virtues of DNA computing and identifies the optimal/near optimal process plan with the help of available resources. Furthermore, in order to investigate the efficacy of the developed architecture, the manufacturing of a prismatic part having 23 operations has been simulated and solved accordingly. Results obtained reveal the superiority of the proposed architecture. [ABSTRACT FROM AUTHOR]

In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emerged as an important tool for knowledge acquisition from the manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been used on the abstracts and keywords of 150 papers to identify the research gaps and find the linkages between knowledge area, knowledge type and the applied data mining tools and techniques. [ABSTRACT FROM AUTHOR]

In this paper, an Adaptive Hierarchical Ant Colony Optimization (AHACO) has been proposed to resolve the traditional machine loading problem in Flexible Manufacturing Systems (FMS). Machine loading is one of the most important issues that is interlinked with the efficiency and utilization of FMS. The machine loading problem is formulated in order to minimize the system unbalance and maximize the throughput, considering the job sequencing, optional machines and technological constraints. The performance of proposed AHACO has been tested over a number of benchmark problems taken from the literature. Computational results indicate that the proposed algorithm is more effective and produces promising results as compared to the existing solution methodologies in the literature. The evaluation and comparison of system efficiency and system utilization justifies the supremacy of the algorithm. Further, results obtained from the proposed algorithm have been compared with well known random search algorithm viz. genetic algorithm, simulated annealing, artificial Immune system, simple ant colony optimization, tabu search etc. In addition, the algorithm has been tested over a randomly generated problem set of varying complexities; the results validate the robustness and scalability of the algorithm utilizing the concepts of ‘heuristic gap’ and ANOVA analysis. [ABSTRACT FROM AUTHOR]

Automated guided vehicles (AGVs) are the most flexible means to transport materials among workstations of a flexible manufacturing system. Complex issues associated with the design of AGV control of these systems are conflict-free shortest path, minimum time motion planning and deadlock avoidance. This research presents an intelligent agent-based framework to overcome the inefficacies associated with the aforementioned issues. Proposed approach describes the operational control of AGVs by integrating different activities such as path generation, journey time enumeration, collision and deadlock identification, waiting node location and its time estimation, and decision making on the selection of the conflict-free shortest feasible path. It represents efficient algorithms and rules associated with each agent for finding the conflict-free minimum time motion planning of AGVs, which are needed to navigate unidirectional and bidirectional flow path network. A collaborative architecture of AGV agent and its different modules are also presented. Three complex experimental scenarios are simulated to test the robustness of the proposed approach. It is shown that the proposed agent-based controller is capable of generating optimal, collision- and deadlock-free path with less computational efforts. [ABSTRACT FROM AUTHOR]

An integrated approach is discussed in this article to solve the sub-problems like tool-part grouping, job allocation on machines and minimization of make-span in a FMS. Tool and part grouping is performed using “principal component analysis”, and tool allocation has been carried out using priority-based approach by developing a potency index. Thereafter, the concept has evolved based on threshold machining time, minimum operation time, and maximum possible operation time to minimize the make-span of the system. In order to validate the result “analysis of variance” has been employed, and on a simulated example the F ratio is enumerated. [ABSTRACT FROM AUTHOR]

An injection or die-casting mould is an assembly of parts containing an impression into which molten material is injected. In this article, the undercuts present in mould parts are divided into basically two parts: completely visible and partially visible. A graph-based approach is proposed to identify these undercuts even for the free form objects. Unlike conventional graph based methods a new polyhedron face adjacency graph (PFAG) is proposed with the key concept of visibility of undercuts by using Bezier surface. A rule-based approach is also discussed to automatically generate an optimal parting surfaceof irregular moulded parts. Since the generation of parting surface plays an important and effective role in mould – die design, thus it is essential to develop a simple and robust algorithm based on proposed methodology, which can effectively tackle the problem. Different case studies show that the proposed method can recognize various undercut features without much difficulty. [ABSTRACT FROM AUTHOR]

A study of indium nanoparticles prepared by two laser ablation techniques is reported. The suspensions of indium nanoparticles were prepared using the laser ablation of bulk indium in liquids. The prepared suspensions of indium nanoparticles were analyzed by the X-ray fluorescence spectroscopy and absorption spectroscopy. The position of the surface plasmon resonance of In-containing suspensions (350 nm) was consistent with the estimations taking into account the average size of In nanoparticles (43 nm) measured using the X-ray fluorescence spectroscopy. The nonlinear optical parameters of indium nanoparticles-containing liquids were studied by the z-scan technique using a picosecond Nd:YAG laser. We compare the laser ablation in liquids with the laser ablation of indium in vacuum at the tight and weak focusing conditions of a Ti:sapphire laser and analyze the 60 nm indium nanoparticles synthesized in the latter case. [ABSTRACT FROM AUTHOR]

Job sequencing and machine loading are two vital and interrelated production planning problems in flexible manufacturing systems (FMSs). In this research, attempts have been made to address the combined job sequencing and machine loading problem using minimization of system unbalance and maximization of throughput as objective functions, while satisfying the constraints related to available machining time and tool slots. This research describes two heuristics to deal with the problems. Heuristic I uses predetermined fixed job sequencing rules as inputs for operation allocation decision on machines, whereas heuristic II uses genetic algorithm based approach for simultaneously addressing job sequences and operation machine allocation issues. Performance of these heuristics has been tested on problems representing three different FMS scenarios. Heuristic II (Genetic algorithm based) has been found more efficient and outperformed heuristic I in terms of solution quality. [ABSTRACT FROM AUTHOR]

Feature recognition systems are now widely identified as a cornerstone for conceiving an automated process planning system. Various techniques have been reported in the literature, but a few of them acquired a status of generic methodology. A flexible and robust approach is demanded for recognising a wide variety of features, e.g., non-interacting, interacting circular and slanting features. This research aims to exploit the concept of the ray - firing technique, in which a 2D surface pattern for each feature is generated and information is extracted from these patterns to correlate it with the corresponding machining features. The system first defines a virtual surface and then probing rays are dropped from each point of this surface to the 2.5D features of the B-rep solid model. According to the length of rays between the bottom face of the 2.5D machining features and the virtual surface, 2D feature patterns are formed for each machining feature. Finally, features are recognised using an algorithm described in this article. Different types of examples have been considered to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In today’s competitive market, manufacturers need to quickly adapt to the changing demands of the customers. Reconfigurable manufacturing system (RMS) is a cost-effective system that can easily absorb frequent changes in product demands. In this article such a system is modelled using expert enhanced coloured fuzzy Petri net (EECFPN), which considers the demands of customers as a fuzzy parameter and vividly captures the reconfigurability aspect of RMS. A fuzzy control strategy (FCS) is proposed to deal with the information delays occurring during information transfer or decision implementation. After intensive computational experimentation, it has been found that FCS outperforms the alternative priority (AP) heuristic and it is considered an effective measure to deal with situations where considerable information delay is involved. [ABSTRACT FROM AUTHOR]

The main problem for an automated guided vehicle (AGV) dispatching system is to assign vehicles to transport demands which optimise some predetermined objectives of a manufacturing shop. This paper presents a framework for an AGV dispatching system based on an object oriented approach using the unified modelling language (UML), and the development of a dispatching algorithm to facilitate a human controller to dispatch efficiently a fleet of AGVs in response to calls from any shop floor (or machine) operator. The main reason for this work is to model an AGV dispatching system as well as to develop a dispatching algorithm which can record details of the AGV position and movement and ensure their allocation of new orders. The provision of both immediate and pre-booked orders for an AGV is also incorporated in the proposed AGVs dispatching system. The underlying AGV dispatching system and algorithm are capable of dispatching a vehicle automatically to handle a call at the required time. In order to overcome difficulties associated with tackling immediate orders, pre-booked orders, and processing of information related to AGVs, a comprehensive dispatching algorithm is developed which aims to minimise lateness, traveling time and distance of empty vehicles in a simulated job-shop scenario. The effectiveness of the proposed framework for an AGV dispatching system is shown through a test problem. [ABSTRACT FROM AUTHOR]

This paper aims to develop a fuzzy-based solution approach to address a machine-loading problem of a flexible manufacturing system (FMS). The proposed solution methodology effectively deals with all the three main constituents of a machine loading problem, viz. job sequence determination, operation machine allocation and the reallocation of jobs. The main objectives of the FMS loading problem considered here are minimisation of system imbalance and maximisation of throughput; the constraints to be satisfied are the available machining time and tool slots. An analytical argument has been provided to support the membership function related to the operation machine allocation vector. Computational results revealed the superiority of the proposed algorithm over other heuristics when it is tested on a standard data set adopted from literature. A new class of petri net model called the “Extended neuro fuzzy petri net” is constructed to capture clearly the various details of the machine loading problem which can be further extended to learn from experience and perform inferences so that truly intelligent system characteristics can be realised. [ABSTRACT FROM AUTHOR]

Nocturnal measurements of air temperature, relative humidity, temperature inversion-layer thickness, water vapour path and visibility-through-fog, made under non-foggy and foggy conditions in winter over two seasons at Delhi, are analysed to study the decrease in both rate of cooling and temperature inversion-layer thickness during the course of nights followed by fog occurrence. In particular, the decrease in the rate of cooling, compared to that on non-foggy nights, is explained as due to the greenhouse warming effect by a layer of excessive, near-saturated water vapour trapped in a temperature inversion. Next, the linear programming technique is employed to forecast the occurrence of fog, where the visibility-through-fog is minimized through its linear regression equation with the pair of variables, mean air temperature and temperature decrease over one hour (measuring rate of cooling at two convenient hours) in the pre-midnight period. This technique provides feasible solutions that enables one to forecast the occurrence of radiative fog. [ABSTRACT FROM AUTHOR]